Improving the Capabilities of Cognitive Radar and EW Systems

Unveil the challenges that mode-agile radar and EW threat emitters pose to traditional static threat library implementations in radar and EW systems, and consider the architecture of cognitive artificial intelligence (AI) and machine learning (ML) systems that can be used to deliver effective RF countermeasures. This whitepaper also explains how a wideband RF record, simulation and playback system can be used to train the AI/ML engines, and evaluates the responses and effectiveness of those countermeasures on real hardware.

Elements of a Cognitive Radar/EW System

Artificial Intelligence and Machine Learning Techniques

Cognitive Radar/EW System

Challenges in Training Cognitive Radar/EW Systems

Acquisition of Dataset

HIL/SIL Training System

White Paper Overview

Unveil the challenges that mode-agile (WARM) radar and EW threat emitters pose to traditional static threat library implementations in radar and EW systems, and consider the architecture of cognitive artificial intelligence (AI) and machine learning (ML) systems that can be used to deliver effective RF countermeasures.

This white paper also explains how a wideband RF record, simulation and playback system can be used to train the AI/ML engines, and evaluates the responses and effectiveness of those countermeasures on real hardware.